| CPC G06N 5/04 (2013.01) [G06N 20/00 (2019.01)] | 20 Claims |

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1. A method of executing a computer-automated process using trained machine learning (ML) models, the method comprising:
using at least one rule set to determine that a first ML model is untrained to characterize a first event type;
modifying the first ML model;
accessing first event data describing a first event of the first event type;
after modifying the first ML model, executing, by one or more hardware processors, the first ML model to determine an ML characterization of the first event using the first event data;
applying, by the one or more hardware processors, a first rule set to the first event data to generate a rule characterization of the first event;
determining, by the one or more hardware processors, an output characterization of the first event based at least in part on the rule characterization of the first event; and
determining, by the one or more hardware processors, to deactivate the first rule set based at least in part on the ML characterization of the first event.
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